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- title -> 'Quarantining Reward-Hacking Gradients with a Hacking Representation' - contributions: (1) adapt SGTM parameter-gradient masking from supervised unlearning to RL reward hacking, route+ablate framing from gradient routing but NOT Cloud's activation .detach(); (2) replace the data-label mask with a RepE-extracted hack direction from ~10-21 pairs (live rollouts unlabeled). - method 'Arms': call route SGTM-style post-backward parameter masking in SVD basis, routed into a deletable subspace. - related work: Cloud = localize-then-ablate idea only; SGTM = closest mechanistic relative, their TPR/FPR knob = our weak-detector axis. - title comment flags the OPEN synthetic-pairs question (headline v_hack is hand-authored prog_wide, not AI-prompted). Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>